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Human Effects of Enhanced Privacy Management Models
ABSTRACT:
We enhance existing and introduce new social network privacy management models and we
measure their human effects. First, we introduce a mechanism using proven clustering techniques
that assists users in grouping their friends for traditional groupbased policy management
approaches. We found measurable agreement between clusters and user-defined relationship
groups. Second, we introduce a new privacy management model that leverages users’ memory
and opinion of their friends (called example friends) to set policies for other similar friends.
Finally, we explore different techniques that aid users in selecting example friends. We found
that by associating policy temples with example friends (versus group labels), users author
policies more efficiently and have improved perceptions over traditional group-based policy
management approaches. In addition, our results show that privacy management models can
further enhanced by utilizing user privacy sentiment for mass customization. By detecting user
privacy sentiment (i.e., an unconcerned user, a pragmatist or a fundamentalist), privacy
management models can be automatically tailored specific to the privacy sentiment and needs of
the user.
EXISTING SYSTEM:
SOCIAL networking sites are experiencing tremendous adoption and growth. The Internet and
online social networks, in particular, are a part of most people’s lives. eMarketer.com reports that
in 2011, nearly 150 million US Internet users will interface with at least one social networking
site per month. eMarketer.com also reports that in 2011, 90 percent of Internet users ages 18-24
and 82 percent of Internet users ages 25-34 will interact with at least one social networking site
per month. This trend is increasing for all age groups. As the young population ages, they will
continue to leverage social media in their daily lives. In addition, new generations will come to
adopt the Internet and online social networks. These technologies have become and will continue
to be a vital component of our social fabric, which we depend on to communicate, interact, and
socialize.

2. DISADVANTAGES OF EXISTING SYSTEM:
 Large amount of content coupled with the significant
number of users online makes maintaining appropriate levels of privacy very challenging.
 Not efficient.
PROPOSED SYSTEM:
First, there are varying levels of privacy controls, depending on the online site. For example,
some sites make available user profile data to the Internet with no ability to restrict access. While
other sites limit user profile viewing to just trusted friends. Other studies introduce the notion of
the privacy paradox, the relationship between individual privacy intentions to disclose their
personal information and their actual behavior. Individuals voice concerns over the lack of
adequate controls around their privacy information while freely providing their personal data.
Other research concludes that individuals lack appropriate information to make informed privacy
decisions. Moreover, when there is adequate information, short-term benefits are often opted
over long-term privacy. However, contrary to common belief, people are concerned about
privacy. But managing ones privacy can be challenging. This can be attributed to many things,
for example, the lack of privacy controls available to the user, the complexity of using the
controls, and the burden associated with managing these controls for large sets of users.
ADVANTAGES OF PROPOSED SYSTEM:
 An incremental improvement to traditional group-based policy management.
 Management—a new paradigm improvement over traditional group-based policy
management.
 An incremental improvement to Same-As Policy Management.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
Processor – Pentium –IV
Speed – 1.1 Ghz
RAM – 512 MB(min)
Hard Disk – 40 GB
Key Board – Standard Windows Keyboard
Mouse – Two or Three Button Mouse

3. Monitor – LCD/LED
SOFTWARE REQUIREMENTS:
Operating system : Windows XP.
Coding Language : JAVA
Data Base : MySQL
Tool : Netbeans.